The RNA-binding protein hnRNPA2 regulates β-catenin protein expression and is overexpressed in prostate cancer
Why this work is in the frame
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Bibliographic record
Abstract
INTRODUCTION: The RNA-binding protein hnRNPA2 (HNRNPA2B1) is upregulated in cancer, where it controls alternative pre-mRNA splicing of cancer-relevant genes. Cytoplasmic hnRNPA2 is reported in aggressive cancers, but is functionally uncharacterized. We explored the role of hnRNPA2 in prostate cancer (PCa). METHODS: hnRNPA2 function/localization/expression in PCa was determined using biochemical approaches (colony forming/proliferation/luciferase reporter assays/flow cytometry/immunohistocytochemistry). Binding of hnRNPA2 within cancer-relevant 3'-UTR mRNAs was identified by bioinformatics. RESULTS: RNAi-mediated knockdown of hnRNPA2 reduced colony forming and proliferation, while hnRNPA2 overexpression increased proliferation of PCa cells. Nuclear hnRNPA2 is overexpressed in high-grade clinical PCa, and is also observed in the cytoplasm in some cases. Ectopic expression of a predominantly cytoplasmic variant hnRNPA2-ΔRGG also increased PCa cell proliferation, suggesting that cytoplasmic hnRNPA2 may also be functionally relevant in PCa. Consistent with its known cytoplasmic roles, hnRNPA2 was associated with 3'-UTR mRNAs of several cancer-relevant mRNAs including β-catenin (CTNNB1). Both wild-type hnRNPA2 and hnRNPA2-ΔRGG act on CTNNB1 3'-UTR mRNA, increasing endogenous CTNNB1 mRNA expression and β-catenin protein expression and nuclear localization. CONCLUSION: Nuclear and cytoplasmic hnRNPA2 are present in PCa and appear to be functionally important. Cytoplasmic hnRNPA2 may affect the cancer cell phenotype through 3'-UTR mRNA-mediated regulation of β-catenin expression and other cancer-relevant genes.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it